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This directory contains PyTorch YOLOv3 software developed by Ultralytics LLC, and is freely available for redistribution under the GPL-3.0 license. For more information please visit https://www.ultralytics.com.

What You Will Learn

  • How to load your custom image detection data from Roboflow
  • How to instatiate a pytorch YOLOv3 model
  • How to train the YOLOv3 model
  • How to use the trained model for quick inference
  • How to save model weights for future use

Resources

  • This blogpost provides a roadmap (though it is tailored to a keras implementation)
  • This notebook provides the code necessary to run the tutorial Open In Colab
  • For reading purposes, the notebook is also saved in Tutorial.ipynb

About Roboflow for Data Management

Roboflow makes managing, preprocessing, augmenting, and versioning datasets for computer vision seamless. Developers reduce 50% of their code when using Roboflow's workflow, automate annotation quality assurance, save training time, and increase model reproducibility.

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YOLOv3 in PyTorch > ONNX > CoreML > iOS

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  • Jupyter Notebook 81.3%
  • Python 11.7%
  • Shell 6.8%
  • Dockerfile 0.2%